Spontaneous Intracerebral Hemorrhage: Factors Predicting Long-Term Mortality After Intensive Care (vol 50, pg 2336, 2019)

Fallenius

STROKE(2022)

引用 23|浏览23
暂无评分
摘要
Background and Purpose- We compared clinical and radiological predictors of long-term mortality in patients with spontaneous intracerebral hemorrhage (ICH) needing intensive care. Methods- A retrospective multicenter study of adult ICH patients treated in Finnish tertiary hospital's intensive care units during 2003 to 2013. We created 3 multivariable models (clinical, radiological, and combined clinical-radiological) for 12-month mortality prediction and compared their areas under receiver operating characteristic curves (AUCs). We analyzed supratentorial and infratentorial ICHs separately. Results- Of 972 patients (796 supratentorial ICH, 176 infratentorial ICH) included, 43% died within 12 months (42% supratentorial ICH, 49% infratentorial ICH). For all patients, the clinical model (AUC, 0.83; 95% CI, 0.81-0.86) outperformed the radiological model (AUC, 0.73; 95% CI, 0.70-0.77; P<0.001), yet the combined model (AUC, 0.85; 95% CI, 0.83-0.88) outperformed both condensed models (P<0.001). For supratentorial ICH, the combined model outperformed both the clinical and radiological models (AUC, 0.84; 95% CI, 0.81-0.87 versus AUC, 0.82; 95% CI, 0.79-0.85 and AUC, 0.73; 95% CI, 0.69-0.77; P<0.001 for all). For infratentorial ICH patients, the combined model significantly outperformed the radiological model but not the clinical model (AUC, 0.92; 95% CI, 0.88-0.96 versus AUC, 0.76; 95% CI, 0.69-0.83 versus AUC, 0.91; 95% CI, 0.87-0.95; PP=0.433, respectively). Conclusions- Clinical factors were more important than objective radiological factors for 12-month mortality prediction in intensive care unit-treated ICH patients. The effect of clinical and radiological factors on outcome was different for supratentorial and infratentorial ICHs stressing that these should not be treated as one entity.
更多
查看译文
关键词
cerebral hemorrhage,critical care,prognosis,risk factors
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要